24 citations · 29 across the 4 of their papers we have counts for
4 papers
Training RL Agents for Multi-Objective Network Defense Tasks
Andres Molina-Markham, Luis Robaina, Sean Steinle +6
Open-ended learning (OEL) -- which emphasizes training agents that achieve broad capability over narrow competency -- is emerging as a paradigm to develop artificial intelligence (…
Evaluating Automated Driving Planner Robustness against Adversarial Influence
Andres Molina-Markham, Silvia G. Ionescu, Erin Lanus +3
Evaluating the robustness of automated driving planners is a critical and challenging task. Although methodologies to evaluate vehicles are well established, they do not yet accoun…
Network Defense is Not a Game
Andres Molina-Markham, Ransom K. Winder, Ahmad Ridley
Research seeks to apply Artificial Intelligence (AI) to scale and extend the capabilities of human operators to defend networks. A fundamental problem that hinders the generalizati…
Network Environment Design for Autonomous Cyberdefense
Andres Molina-Markham, Cory Miniter, Becky Powell +1
Reinforcement learning (RL) has been demonstrated suitable to develop agents that play complex games with human-level performance. However, it is not understood how to effectively…